class_docstr: Unit test for posterior sampling with Gaussian likelihood and Gaussian prior
class_docstr_tok: ["Unit","test","for","posterior","sampling","with","Gaussian","likelihood","and","Gaussian","prior"]
docstr: Compute log pdf of model 
docstr_tok: ["Compute","log","pdf","of","model"]
code: def _logp(self, x):
      """Compute log pdf of model"""
      dist = Normal(x, self.var)
      val = self.prior.logp(x)
      for i in range(len(self.data)):
          val = val + dist.logp(self.data[i])
      return val
  
file_path: dragonfly/dragonfly/distributions/unittest_posterior.py
imports: from __future__ import absolute_import
  from __future__ import division
  import unittest
  import numpy
  from .continuous import Normal
  from .model import Model
  from ..utils.base_test_class import BaseTestClass, execute_tests
label_desc: Use image node_id 6 for calling the PosteriorTestCase obj's underlying member method code with example usage: obj._logp(x) and returns: val